Pancreatic cancer is an almost uniformly fatal disease that will strike -33,000 families in the United States this year. It has been estimated that 5-10% of these cancers have a familial basis. A better understanding of the genetic basis for the familial aggregation of pancreatic cancer will form a foundation for counseling patients and their families, a basis for the rational application of new tests to detect this disease earlier, and may lead to gene-specific therapies. This project builds on progress made and collaborations established during the last funding period of this Gl SPORE in which we demonstrated: a) that individuals with a strong family history of pancreatic cancer have a significantly increased risk of developing pancreatic cancer, b) that these at-risk individuals can be screened by endoscopic ultrasound for early neoplasia, c) that this early neoplasia has a distinct phenotype, d) that germ-line mutations in BRCA2 and other members of the Fanconi anemia pathway are associated with an increased risk of developing pancreatic cancer, and e) that cancers with these mutations are selectively sensitive to gene-specific therapies. We now propose to: 1) define the patterns of clustering of pancreatic and non-pancreatic cancers in families and to use these data to develop a risk prediction tool (PancPRO) for clinical use, 2) perform a case-control genome wide association study on familial pancreatic cancer kindreds of Ashkenazi Jewish descent, and 3) determine the gene(s) responsible for the familial clustering of pancreatic cancer. The studies proposed here directly address a research priority identified in the NCI Pancreatic Cancer Program Review Group (PRG) - "Identify genetic factors, environmental factors, and gene-environment interactions that contribute to pancreatic cancer development." The studies proposed will utilize tissues and families from the Cores (Core 2 and Core 3) to translate genetic discoveries made in Project 1B and 3C to patient care and they will provide a scientific basis for the selection of patients